Man-Machine-Synchrony

The focus of this (provocative) position paper is on how humans and ‘learning’ machines team up. Specifically, we look into the concept of synchrony. Systems ‘in sync’ seem to perform better. Using hyperscanning methods from social neuroscience one may analyse if humans are ‘in sync’. We suggest that this methodology might be applicable to study man-machine teaming as well. We hypothesize that various implementations of artificial neural nets lead to different levels of synchronizations with humans.